AI
10 Generative AI Challenges and How to Overcome Them
Generative AI often looks ready to deploy, demos impress, and pilots succeed, yet when businesses attempt to move from proof of concept to production, projects stall. Costs rise, data pipelines falter, compliance hurdles mount, and leaders demand returns that are difficult to prove. These generative challenges across technology, finance, data, and trust are the real barriers to moving from pilot to production. According to Gartner, at least 30% of generative AI projects will be abandoned after proof of concept by the end of 2025 .
